.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorials/audio_resampling_tutorial.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_tutorials_audio_resampling_tutorial.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_tutorials_audio_resampling_tutorial.py:


Audio Resampling
================

**Author**: `Caroline Chen <carolinechen@meta.com>`__, `Moto Hira <moto@meta.com>`__

This tutorial shows how to use torchaudio's resampling API.

.. GENERATED FROM PYTHON SOURCE LINES 10-19

.. code-block:: default


    import torch
    import torchaudio
    import torchaudio.functional as F
    import torchaudio.transforms as T

    print(torch.__version__)
    print(torchaudio.__version__)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    2.6.0
    2.6.0




.. GENERATED FROM PYTHON SOURCE LINES 20-25

Preparation
-----------

First, we import the modules and define the helper functions.


.. GENERATED FROM PYTHON SOURCE LINES 25-110

.. code-block:: default


    import math
    import timeit

    import librosa
    import matplotlib.colors as mcolors
    import matplotlib.pyplot as plt
    import pandas as pd
    import resampy
    from IPython.display import Audio

    pd.set_option("display.max_rows", None)
    pd.set_option("display.max_columns", None)

    DEFAULT_OFFSET = 201


    def _get_log_freq(sample_rate, max_sweep_rate, offset):
        """Get freqs evenly spaced out in log-scale, between [0, max_sweep_rate // 2]

        offset is used to avoid negative infinity `log(offset + x)`.

        """
        start, stop = math.log(offset), math.log(offset + max_sweep_rate // 2)
        return torch.exp(torch.linspace(start, stop, sample_rate, dtype=torch.double)) - offset


    def _get_inverse_log_freq(freq, sample_rate, offset):
        """Find the time where the given frequency is given by _get_log_freq"""
        half = sample_rate // 2
        return sample_rate * (math.log(1 + freq / offset) / math.log(1 + half / offset))


    def _get_freq_ticks(sample_rate, offset, f_max):
        # Given the original sample rate used for generating the sweep,
        # find the x-axis value where the log-scale major frequency values fall in
        times, freq = [], []
        for exp in range(2, 5):
            for v in range(1, 10):
                f = v * 10**exp
                if f < sample_rate // 2:
                    t = _get_inverse_log_freq(f, sample_rate, offset) / sample_rate
                    times.append(t)
                    freq.append(f)
        t_max = _get_inverse_log_freq(f_max, sample_rate, offset) / sample_rate
        times.append(t_max)
        freq.append(f_max)
        return times, freq


    def get_sine_sweep(sample_rate, offset=DEFAULT_OFFSET):
        max_sweep_rate = sample_rate
        freq = _get_log_freq(sample_rate, max_sweep_rate, offset)
        delta = 2 * math.pi * freq / sample_rate
        cummulative = torch.cumsum(delta, dim=0)
        signal = torch.sin(cummulative).unsqueeze(dim=0)
        return signal


    def plot_sweep(
        waveform,
        sample_rate,
        title,
        max_sweep_rate=48000,
        offset=DEFAULT_OFFSET,
    ):
        x_ticks = [100, 500, 1000, 5000, 10000, 20000, max_sweep_rate // 2]
        y_ticks = [1000, 5000, 10000, 20000, sample_rate // 2]

        time, freq = _get_freq_ticks(max_sweep_rate, offset, sample_rate // 2)
        freq_x = [f if f in x_ticks and f <= max_sweep_rate // 2 else None for f in freq]
        freq_y = [f for f in freq if f in y_ticks and 1000 <= f <= sample_rate // 2]

        figure, axis = plt.subplots(1, 1)
        _, _, _, cax = axis.specgram(waveform[0].numpy(), Fs=sample_rate)
        plt.xticks(time, freq_x)
        plt.yticks(freq_y, freq_y)
        axis.set_xlabel("Original Signal Frequency (Hz, log scale)")
        axis.set_ylabel("Waveform Frequency (Hz)")
        axis.xaxis.grid(True, alpha=0.67)
        axis.yaxis.grid(True, alpha=0.67)
        figure.suptitle(f"{title} (sample rate: {sample_rate} Hz)")
        plt.colorbar(cax)









.. GENERATED FROM PYTHON SOURCE LINES 111-147

Resampling Overview
-------------------

To resample an audio waveform from one freqeuncy to another, you can use
:py:class:`torchaudio.transforms.Resample` or
:py:func:`torchaudio.functional.resample`.
``transforms.Resample`` precomputes and caches the kernel used for resampling,
while ``functional.resample`` computes it on the fly, so using
``torchaudio.transforms.Resample`` will result in a speedup when resampling
multiple waveforms using the same parameters (see Benchmarking section).

Both resampling methods use `bandlimited sinc
interpolation <https://ccrma.stanford.edu/~jos/resample/>`__ to compute
signal values at arbitrary time steps. The implementation involves
convolution, so we can take advantage of GPU / multithreading for
performance improvements.

.. note::

   When using resampling in multiple subprocesses, such as data loading
   with multiple worker processes, your application might create more
   threads than your system can handle efficiently.
   Setting ``torch.set_num_threads(1)`` might help in this case.

Because a finite number of samples can only represent a finite number of
frequencies, resampling does not produce perfect results, and a variety
of parameters can be used to control for its quality and computational
speed. We demonstrate these properties through resampling a logarithmic
sine sweep, which is a sine wave that increases exponentially in
frequency over time.

The spectrograms below show the frequency representation of the signal,
where the x-axis corresponds to the frequency of the original
waveform (in log scale), y-axis the frequency of the
plotted waveform, and color intensity the amplitude.


.. GENERATED FROM PYTHON SOURCE LINES 147-154

.. code-block:: default


    sample_rate = 48000
    waveform = get_sine_sweep(sample_rate)

    plot_sweep(waveform, sample_rate, title="Original Waveform")
    Audio(waveform.numpy()[0], rate=sample_rate)




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_001.png
   :alt: Original Waveform (sample rate: 48000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_001.png
   :class: sphx-glr-single-img



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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 155-162

Now we resample (downsample) it.

We see that in the spectrogram of the resampled waveform, there is an
artifact, which was not present in the original waveform.
This effect is called aliasing.
`This page <https://music.arts.uci.edu/dobrian/digitalaudio.htm>`__ has
an explanation of how it happens, and why it looks like a reflection.

.. GENERATED FROM PYTHON SOURCE LINES 163-171

.. code-block:: default


    resample_rate = 32000
    resampler = T.Resample(sample_rate, resample_rate, dtype=waveform.dtype)
    resampled_waveform = resampler(waveform)

    plot_sweep(resampled_waveform, resample_rate, title="Resampled Waveform")
    Audio(resampled_waveform.numpy()[0], rate=resample_rate)




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_002.png
   :alt: Resampled Waveform (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_002.png
   :class: sphx-glr-single-img



.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source 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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 172-186

Controling resampling quality with parameters
---------------------------------------------

Lowpass filter width
~~~~~~~~~~~~~~~~~~~~

Because the filter used for interpolation extends infinitely, the
``lowpass_filter_width`` parameter is used to control for the width of
the filter to use to window the interpolation. It is also referred to as
the number of zero crossings, since the interpolation passes through
zero at every time unit. Using a larger ``lowpass_filter_width``
provides a sharper, more precise filter, but is more computationally
expensive.


.. GENERATED FROM PYTHON SOURCE LINES 186-193

.. code-block:: default


    sample_rate = 48000
    resample_rate = 32000

    resampled_waveform = F.resample(waveform, sample_rate, resample_rate, lowpass_filter_width=6)
    plot_sweep(resampled_waveform, resample_rate, title="lowpass_filter_width=6")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_003.png
   :alt: lowpass_filter_width=6 (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_003.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 195-199

.. code-block:: default


    resampled_waveform = F.resample(waveform, sample_rate, resample_rate, lowpass_filter_width=128)
    plot_sweep(resampled_waveform, resample_rate, title="lowpass_filter_width=128")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_004.png
   :alt: lowpass_filter_width=128 (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_004.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 200-211

Rolloff
~~~~~~~

The ``rolloff`` parameter is represented as a fraction of the Nyquist
frequency, which is the maximal frequency representable by a given
finite sample rate. ``rolloff`` determines the lowpass filter cutoff and
controls the degree of aliasing, which takes place when frequencies
higher than the Nyquist are mapped to lower frequencies. A lower rolloff
will therefore reduce the amount of aliasing, but it will also reduce
some of the higher frequencies.


.. GENERATED FROM PYTHON SOURCE LINES 211-219

.. code-block:: default



    sample_rate = 48000
    resample_rate = 32000

    resampled_waveform = F.resample(waveform, sample_rate, resample_rate, rolloff=0.99)
    plot_sweep(resampled_waveform, resample_rate, title="rolloff=0.99")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_005.png
   :alt: rolloff=0.99 (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_005.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 221-226

.. code-block:: default


    resampled_waveform = F.resample(waveform, sample_rate, resample_rate, rolloff=0.8)
    plot_sweep(resampled_waveform, resample_rate, title="rolloff=0.8")





.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_006.png
   :alt: rolloff=0.8 (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_006.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 227-237

Window function
~~~~~~~~~~~~~~~

By default, ``torchaudio``’s resample uses the Hann window filter, which is
a weighted cosine function. It additionally supports the Kaiser window,
which is a near optimal window function that contains an additional
``beta`` parameter that allows for the design of the smoothness of the
filter and width of impulse. This can be controlled using the
``resampling_method`` parameter.


.. GENERATED FROM PYTHON SOURCE LINES 237-245

.. code-block:: default



    sample_rate = 48000
    resample_rate = 32000

    resampled_waveform = F.resample(waveform, sample_rate, resample_rate, resampling_method="sinc_interp_hann")
    plot_sweep(resampled_waveform, resample_rate, title="Hann Window Default")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_007.png
   :alt: Hann Window Default (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_007.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 247-252

.. code-block:: default


    resampled_waveform = F.resample(waveform, sample_rate, resample_rate, resampling_method="sinc_interp_kaiser")
    plot_sweep(resampled_waveform, resample_rate, title="Kaiser Window Default")





.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_008.png
   :alt: Kaiser Window Default (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_008.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 253-259

Comparison against librosa
--------------------------

``torchaudio``’s resample function can be used to produce results similar to
that of librosa (resampy)’s kaiser window resampling, with some noise


.. GENERATED FROM PYTHON SOURCE LINES 259-263

.. code-block:: default


    sample_rate = 48000
    resample_rate = 32000








.. GENERATED FROM PYTHON SOURCE LINES 264-267

kaiser_best
~~~~~~~~~~~


.. GENERATED FROM PYTHON SOURCE LINES 267-278

.. code-block:: default

    resampled_waveform = F.resample(
        waveform,
        sample_rate,
        resample_rate,
        lowpass_filter_width=64,
        rolloff=0.9475937167399596,
        resampling_method="sinc_interp_kaiser",
        beta=14.769656459379492,
    )
    plot_sweep(resampled_waveform, resample_rate, title="Kaiser Window Best (torchaudio)")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_009.png
   :alt: Kaiser Window Best (torchaudio) (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_009.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 280-286

.. code-block:: default


    librosa_resampled_waveform = torch.from_numpy(
        librosa.resample(waveform.squeeze().numpy(), orig_sr=sample_rate, target_sr=resample_rate, res_type="kaiser_best")
    ).unsqueeze(0)
    plot_sweep(librosa_resampled_waveform, resample_rate, title="Kaiser Window Best (librosa)")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_010.png
   :alt: Kaiser Window Best (librosa) (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_010.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 288-292

.. code-block:: default


    mse = torch.square(resampled_waveform - librosa_resampled_waveform).mean().item()
    print("torchaudio and librosa kaiser best MSE:", mse)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    torchaudio and librosa kaiser best MSE: 2.0806901153660115e-06




.. GENERATED FROM PYTHON SOURCE LINES 293-296

kaiser_fast
~~~~~~~~~~~


.. GENERATED FROM PYTHON SOURCE LINES 296-307

.. code-block:: default

    resampled_waveform = F.resample(
        waveform,
        sample_rate,
        resample_rate,
        lowpass_filter_width=16,
        rolloff=0.85,
        resampling_method="sinc_interp_kaiser",
        beta=8.555504641634386,
    )
    plot_sweep(resampled_waveform, resample_rate, title="Kaiser Window Fast (torchaudio)")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_011.png
   :alt: Kaiser Window Fast (torchaudio) (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_011.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 309-315

.. code-block:: default


    librosa_resampled_waveform = torch.from_numpy(
        librosa.resample(waveform.squeeze().numpy(), orig_sr=sample_rate, target_sr=resample_rate, res_type="kaiser_fast")
    ).unsqueeze(0)
    plot_sweep(librosa_resampled_waveform, resample_rate, title="Kaiser Window Fast (librosa)")




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_012.png
   :alt: Kaiser Window Fast (librosa) (sample rate: 32000 Hz)
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_012.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 317-321

.. code-block:: default


    mse = torch.square(resampled_waveform - librosa_resampled_waveform).mean().item()
    print("torchaudio and librosa kaiser fast MSE:", mse)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    torchaudio and librosa kaiser fast MSE: 2.5200744248601437e-05




.. GENERATED FROM PYTHON SOURCE LINES 322-332

Performance Benchmarking
------------------------

Below are benchmarks for downsampling and upsampling waveforms between
two pairs of sampling rates. We demonstrate the performance implications
that the ``lowpass_filter_width``, window type, and sample rates can
have. Additionally, we provide a comparison against ``librosa``\ ’s
``kaiser_best`` and ``kaiser_fast`` using their corresponding parameters
in ``torchaudio``.


.. GENERATED FROM PYTHON SOURCE LINES 332-337

.. code-block:: default


    print(f"torchaudio: {torchaudio.__version__}")
    print(f"librosa: {librosa.__version__}")
    print(f"resampy: {resampy.__version__}")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    torchaudio: 2.6.0
    librosa: 0.10.0
    resampy: 0.2.2




.. GENERATED FROM PYTHON SOURCE LINES 339-373

.. code-block:: default



    def benchmark_resample_functional(
        waveform,
        sample_rate,
        resample_rate,
        lowpass_filter_width=6,
        rolloff=0.99,
        resampling_method="sinc_interp_hann",
        beta=None,
        iters=5,
    ):
        return (
            timeit.timeit(
                stmt="""
    torchaudio.functional.resample(
        waveform,
        sample_rate,
        resample_rate,
        lowpass_filter_width=lowpass_filter_width,
        rolloff=rolloff,
        resampling_method=resampling_method,
        beta=beta,
    )
            """,
                setup="import torchaudio",
                number=iters,
                globals=locals(),
            )
            * 1000
            / iters
        )









.. GENERATED FROM PYTHON SOURCE LINES 375-412

.. code-block:: default



    def benchmark_resample_transforms(
        waveform,
        sample_rate,
        resample_rate,
        lowpass_filter_width=6,
        rolloff=0.99,
        resampling_method="sinc_interp_hann",
        beta=None,
        iters=5,
    ):
        return (
            timeit.timeit(
                stmt="resampler(waveform)",
                setup="""
    import torchaudio

    resampler = torchaudio.transforms.Resample(
        sample_rate,
        resample_rate,
        lowpass_filter_width=lowpass_filter_width,
        rolloff=rolloff,
        resampling_method=resampling_method,
        dtype=waveform.dtype,
        beta=beta,
    )
    resampler.to(waveform.device)
            """,
                number=iters,
                globals=locals(),
            )
            * 1000
            / iters
        )









.. GENERATED FROM PYTHON SOURCE LINES 414-443

.. code-block:: default



    def benchmark_resample_librosa(
        waveform,
        sample_rate,
        resample_rate,
        res_type=None,
        iters=5,
    ):
        waveform_np = waveform.squeeze().numpy()
        return (
            timeit.timeit(
                stmt="""
    librosa.resample(
        waveform_np,
        orig_sr=sample_rate,
        target_sr=resample_rate,
        res_type=res_type,
    )
            """,
                setup="import librosa",
                number=iters,
                globals=locals(),
            )
            * 1000
            / iters
        )









.. GENERATED FROM PYTHON SOURCE LINES 445-495

.. code-block:: default



    def benchmark(sample_rate, resample_rate):
        times, rows = [], []
        waveform = get_sine_sweep(sample_rate).to(torch.float32)

        args = (waveform, sample_rate, resample_rate)

        # sinc 64 zero-crossings
        f_time = benchmark_resample_functional(*args, lowpass_filter_width=64)
        t_time = benchmark_resample_transforms(*args, lowpass_filter_width=64)
        times.append([None, f_time, t_time])
        rows.append("sinc (width 64)")

        # sinc 6 zero-crossings
        f_time = benchmark_resample_functional(*args, lowpass_filter_width=16)
        t_time = benchmark_resample_transforms(*args, lowpass_filter_width=16)
        times.append([None, f_time, t_time])
        rows.append("sinc (width 16)")

        # kaiser best
        kwargs = {
            "lowpass_filter_width": 64,
            "rolloff": 0.9475937167399596,
            "resampling_method": "sinc_interp_kaiser",
            "beta": 14.769656459379492,
        }
        lib_time = benchmark_resample_librosa(*args, res_type="kaiser_best")
        f_time = benchmark_resample_functional(*args, **kwargs)
        t_time = benchmark_resample_transforms(*args, **kwargs)
        times.append([lib_time, f_time, t_time])
        rows.append("kaiser_best")

        # kaiser fast
        kwargs = {
            "lowpass_filter_width": 16,
            "rolloff": 0.85,
            "resampling_method": "sinc_interp_kaiser",
            "beta": 8.555504641634386,
        }
        lib_time = benchmark_resample_librosa(*args, res_type="kaiser_fast")
        f_time = benchmark_resample_functional(*args, **kwargs)
        t_time = benchmark_resample_transforms(*args, **kwargs)
        times.append([lib_time, f_time, t_time])
        rows.append("kaiser_fast")

        df = pd.DataFrame(times, columns=["librosa", "functional", "transforms"], index=rows)
        return df









.. GENERATED FROM PYTHON SOURCE LINES 497-507

.. code-block:: default

    def plot(df):
        print(df.round(2))
        ax = df.plot(kind="bar")
        plt.ylabel("Time Elapsed [ms]")
        plt.xticks(rotation=0, fontsize=10)
        for cont, col, color in zip(ax.containers, df.columns, mcolors.TABLEAU_COLORS):
            label = ["N/A" if v != v else str(v) for v in df[col].round(2)]
            ax.bar_label(cont, labels=label, color=color, fontweight="bold", fontsize="x-small")









.. GENERATED FROM PYTHON SOURCE LINES 508-510

Downsample (48 -> 44.1 kHz)
~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 511-515

.. code-block:: default


    df = benchmark(48_000, 44_100)
    plot(df)




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_013.png
   :alt: audio resampling tutorial
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_013.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

                     librosa  functional  transforms
    sinc (width 64)      NaN        0.90        0.40
    sinc (width 16)      NaN        0.72        0.35
    kaiser_best        83.91        1.21        0.38
    kaiser_fast         7.89        0.95        0.34




.. GENERATED FROM PYTHON SOURCE LINES 516-518

Downsample (16 -> 8 kHz)
~~~~~~~~~~~~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 519-523

.. code-block:: default


    df = benchmark(16_000, 8_000)
    plot(df)




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_014.png
   :alt: audio resampling tutorial
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_014.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

                     librosa  functional  transforms
    sinc (width 64)      NaN        1.29        1.10
    sinc (width 16)      NaN        0.54        0.37
    kaiser_best        11.29        1.36        1.17
    kaiser_fast         3.14        0.67        0.41




.. GENERATED FROM PYTHON SOURCE LINES 524-526

Upsample (44.1 -> 48 kHz)
~~~~~~~~~~~~~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 527-531

.. code-block:: default


    df = benchmark(44_100, 48_000)
    plot(df)




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_015.png
   :alt: audio resampling tutorial
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_015.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

                     librosa  functional  transforms
    sinc (width 64)      NaN        0.87        0.36
    sinc (width 16)      NaN        0.70        0.34
    kaiser_best        32.74        1.14        0.38
    kaiser_fast         7.88        0.94        0.34




.. GENERATED FROM PYTHON SOURCE LINES 532-534

Upsample (8 -> 16 kHz)
~~~~~~~~~~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 535-539

.. code-block:: default


    df = benchmark(8_000, 16_000)
    plot(df)




.. image-sg:: /tutorials/images/sphx_glr_audio_resampling_tutorial_016.png
   :alt: audio resampling tutorial
   :srcset: /tutorials/images/sphx_glr_audio_resampling_tutorial_016.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

                     librosa  functional  transforms
    sinc (width 64)      NaN        0.70        0.46
    sinc (width 16)      NaN        0.38        0.22
    kaiser_best        11.24        0.71        0.48
    kaiser_fast         2.99        0.41        0.24




.. GENERATED FROM PYTHON SOURCE LINES 540-554

Summary
~~~~~~~

To elaborate on the results:

- a larger ``lowpass_filter_width`` results in a larger resampling kernel,
  and therefore increases computation time for both the kernel computation
  and convolution
- using ``sinc_interp_kaiser`` results in longer computation times than the default
  ``sinc_interp_hann`` because it is more complex to compute the intermediate
  window values
- a large GCD between the sample and resample rate will result
  in a simplification that allows for a smaller kernel and faster kernel computation.



.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  3.361 seconds)


.. _sphx_glr_download_tutorials_audio_resampling_tutorial.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example


    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: audio_resampling_tutorial.py <audio_resampling_tutorial.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: audio_resampling_tutorial.ipynb <audio_resampling_tutorial.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_